Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 103). / Modular engineering allows the creation of a product architecture that prepares the product families of companies for a fast response to changes in technology and customer demand. This thesis will focus on developing and proposing a methodology for implementing modular engineering at AIP's portfolio companies and ensure that the implementation is replicable in any other of its companies. AIP companies are from very diverse industries and offer multiple heterogeneous products. The proposed methodology will make it possible to target companies and products that are good candidates for the implementation of modularity from the standpoint of cost benefit. One AIP portfolio company is currently implementing modular engineering. This project was the base for creating a use case. This thesis explores the methodology used by the portfolio company for designing a modular architecture and proposes an automated approach using machine learning techniques. This will allow a faster creation and evaluation of the modular architecture. In addition, the modular project benefits are: fewer unique part numbers, less assembly time, lower direct purchasing costs, fewer suppliers, faster time to market, shorter lead-time and more market offerings. The bottom line benefit is a streamlined operation that would add value to the company. Finally, this thesis summarizes the lessons learned of the modular engineering implementation to serve as a guide for future implementations on portfolio companies. / by Chen Josué Arámbula González. / M.B.A. / S.M.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 57-58). / Firms developing an Operations Strategy need to make decisions across a wide spectrum. Within the field of operations strategy, common practice defines the stratification of these decisions into structural and infrastructural elements. Structural decisions relating to the amount of capacity and facilities a firm deploys can impact a firm's cost competitiveness if implemented incorrectly because of the large capital expenditures and time horizons involved. Boston Scientific, a medical device manufacturer, recognizes the importance of operations strategy in achieving competitive success and continually seeks tools that assist in the creation of strategy as it pursues growth. This thesis discusses the development of a scenario planning tool that is focused on estimation of manufacturing footprint requirements for the company's internal manufacturing network. The tool we develop takes a demand forecast as an input and converts it to a physical space requirement in square feet. Additionally, the tool exhibits significant flexibility in being able to develop multiple scenarios, especially given the ability to modify parameters ranging from growth rates to improvement factors within facilities. The tool also offers a deeper level of detail than previously available, with the critical decision unit being the value stream, rather than an aggregation of data to only present factory or network level results. Whilst this work is applied to the context of a medical device manufacturer, the methodology is easily transferable to a range of industries. The work can be applied to any manufacturing setting where investment decisions for new facilities take significant time and capital. Our research of the literature on this topic identified a gap, and the development of the tool is a positive addition to the field of estimation of manufacturing footprint. / by Benjamin Martin Onyango Awuondo. / M.B.A. / S.M.

Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 55). / The MGH Emergency Department (ED) and General Medicine Floor currently experience heavy patient volume and rising patient wait times, despite recent capacity expansions. While several projects have been piloted to divert patients towards alternative care paths, MGH management wants to better understand what types of patients are being admitted to the hospital and what features are deterministic of patient admission. This thesis addresses this information gap by using binary logistic regression models to assess predictive and significant patient features for admission. Our analysis uses both patient demographic information and decision point data gathered in the Emergency Department of patient visits. On out-of-sample data, our predictive model achieves an area under the receiver operating characteristic of 0.82, and we conclude that the predictive features for admission are within good clinical practice. Further analysis of patient care suggests that provision of IV antibiotics in the outpatient setting could reduce MGH admissions by approximately 307 bed-days per year, with additional possible reductions in excess of 1,000 beddays for different provisions of care. We also assess the outpatient usage of MGH patients and conclude that 75 percent of cellulitis, pneumonia and urinary tract infection patients are not seeing a clinician in the outpatient setting prior to ED presentation. This analysis indicates that more proactive management of these patients could prevent both their visit to the ED and potentially their admission. We demonstrate that statistical methods based on real time patient data. can contribute to effective healthcare planning and operations. / by Philip T. Ebben. / S.M. / M.B.A.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 56-57). / For many biotech drugs, minimal competition has led to significant margins. Genentech's legacy product, however, faces intense competition from six other competitors. Competition necessitates contracting to ensure patient access to the product but this results in price erosion. An increase in discounting and subsequent price erosion in recent years has prompted a need to better understand account level profitability. Given a highly dynamic and complex payer and distribution network, it is difficult to determine the contribution of each vial that is sold, such that the profitability of some vials is in question. As other biotech drugs begin to face similar competitive market dynamics, an analysis of Genentech's product brings timely insight into understanding and managing profitability in a competitive environment within the biotechnology sector. System dynamics modeling is used to analyze the key attributes of a competitive environment. It highlights two important and related observations: that increased market share does not necessarily lead to increased profitability, and that contract wins do not always result in increased sales. A framework is introduced to determine account level profitability. By using activity-based accounting to allocate costs, the true profit of each account is determined. Results show that the degree of profitability varies widely, further reinforcing the notion that account specific profits rather than average profits are a more accurate measure of performance. Finally, to assist decision makers in the ongoing process of promoting sound business decisions, tools are created that incorporate the insights gained in this analysis. Both an account specific marginal profit model and a dashboard will help to ensure that future decisions lead to long-term profitability. / by Amy C. Lin. / S.M. / M.B.A.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2010. / "June 2010." Cataloged from PDF version of thesis. / Includes bibliographical references (p. 64). / This thesis investigates the use of a task-based Monte Carlo simulation model to forecast headcount and manufacturing capacity requirements for a drug development organization. A pharmaceutical drug development group is responsible for designing the manufacturing process for new potential drug products, testing the product quality, and supplying product for clinical trials. The drug development process is complex and uncertain. The speed to market is critical to a company's success. Therefore, it is important to have an adequate number of employees and available manufacturing capacity to support timely and efficient drug development. The employees and manufacturing capacity can either be supplied internally or externally, through contract manufacturing organizations. This thesis formulates and empirically evaluates a simulation model designed using the Novartis Biologics drug development process and is adaptable to other pharmaceutical organization. The model demonstrates 7% accuracy when compared with historical data, and estimates within 13% of the currently accepted manufacturing capacity forecasting tool. Additionally, three case studies are included to demonstrate how the model can be used to evaluate strategic decisions. The case studies include: a drug development process improvement evaluation, an outsourcing evaluation, and an "at risk" development evaluation. / by Angela Thedinga. / S.M. / M.B.A.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 81-82). / Successful research and development is critical in ensuring firms continue to meet customer needs and stay ahead of their competition. Hundreds of billions of dollars are spent every year on these R&D pursuits. It may seem logical that the more money a company spends on R&D, the more successful they will be. However, multiple studies have shown there is no significant correlation between a firm's R&D expenditures and its financial performance. The key to effective R&D is not how much a firm spends, but how well the money is spent. There are two sides of doing R&D effectively-doing the right projects and doing projects right. This thesis focuses primarily on the first side, creating a process to help a company choose the best projects to pursue. A significant amount of literature exists in this area, however that literature mostly focuses on R&D performed at original equipment manufacturers (OEMs). For OEMs, R&D is the first step in a product development process where the company has the ultimate decision over the form their product takes. This thesis expands on that literature to focus on R&D project selection for firms that act as suppliers to OEMs. Suppliers performing R&D are faced with significant additional challenges due to the OEM having final say over the product configuration. Suppliers have uncertainties about whether they are pursuing the right technology along with whether they will actually win business to utilize that technology. This fact often forces suppliers to adopt a conservative R&D strategy with a fairly secure likelihood of adoption over speculative R&D that might not come to fruition. Because every company and every industry is different and has different priorities for their R&D activities, there is no single process that will work at every company to help them choose a better portfolio of R&D projects. Instead, this thesis presents a set of guidelines that can be used to help companies (especially suppliers with conservative R&D strategies) design their own process. Along with those guidelines, a case study is presented based on implementing an R&D project selection process at Spirit AeroSystems. The process that was implemented, along with problems encountered with that process and ideas for further improvements are discussed. Lessons learned from Spirit AeroSystems can further be utilized to help companies create better project selection processes. / by Jeremy Pitts. / M.B.A. / S.M.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2012. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 71-75). / Product companies face new challenges as they continue to expand their international footprints. Whereas globalization initially sought savings by outsourcing production to low-cost regions, emerging markets now present new sales opportunities with unique customer demands. Companies increasingly must be sensitive to local expectations at the same time that products are becoming more technology rich and with shorter life cycles. Improved coordination that enables greater speed, flexibility, and multi-market effectiveness is particularly important as companies shift engineering and commercial responsibilities to formerly production-only centers. This study develops and demonstrates an approach to one domain of coordination-the flow of material and related information between globally distributed sites-based on lessons from engineer-to- order (ETO) operating models. By examining contemporary trends in ETO and identifying several generalizable tensions, this study outlines key parameters that distinguish dynamic coordination needs from those embedded in conventional process improvement frameworks. The five-step approach developed in this paper takes a dynamic systems perspective on organizational interfaces and seeks to build feedback mechanisms at multiple levels. It targets the knowledge-transfer, business planning, and execution levels of material management while also addressing the behavioral and practical components of implementation. In doing so, the approach recognizes that uneven process maturity and uncertain external demands must be accommodated. It argues that traditional approaches to coordination have had limited success, because they are slow to adapt and encourage circumvention. Whereas these past methods have exchanged reduced process "waste" for greatly increased rigidity and process housekeeping, the proposed method seeks reinforcing loops that align stakeholders without exhaustive process definition or significant maintenance. A detailed case study at a global ETO business group illustrates the method and its initial results in an environment of limited patience for formal process development. The resulting portfolio of change initiatives, which includes inter-site service level commitments, local forecast sharing, service parts forecasting, and reverse logistics, demonstrates an integrative approach to business site interfaces that attempts to tie local short-term performance with global long-term success. / by Brian S. Hendrickson. / S.M. / M.B.A.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 56-57). / Compared to legacy retailers, online retailers have the potential to better accommodate buyer needs by offering more service time and inventory options. One fundamental operational challenge faced by most online businesses is designing a cost effective distribution network. Based on a fixed number of locations with finite resources, companies strive for finding the cost minimizing formula for fulfilling each customer order while meeting rigorous time constraints. In practice this involves allocating specific geographies to each warehouse and defining the logistic routes serving each customer. In an attempt to address this question, a Mixed Integer Linear Programming model has been developed as a decisionmaking tool for determining the optimal carrier-destination combination at each facility. The resulting algorithm is capable of analyzing thousands of potential shipping lanes and selecting those that minimize overall shipping cost. Based on historical data from customer orders, the model consistently finds an optimal network configuration yielding operational savings on the order of 1.5%. Furthermore, the algorithm can be used to identify near-optimal solutions requiring minor tweaks on the current configuration that produce significant economic gains. This simulation tool can be used on a regular basis to adapt the outbound network to demand fluctuations. However, this phenomenon evinces the existence of a fine trade-off between economic gains and operational feasibility. For that reason, a heuristic for selecting the most robust solution is also proposed. / by David Guasch Rodriguez. / S.M. / M.B.A.

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2013. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 82-83). / Boeing South Carolina builds the Boeing 787 Dreamliner, the world's first composite-skinned wide-body jet. This new manufacturing facility is evolving to meet the demands of building this complex aircraft. One of the challenges faced by this site is providing the manufacturing workforce with the best tools for the job in an efficient manner. Two different research streams investigate this high-level problem. First is a technical investigation into the selection of a cutter (drill bit) for use in drilling Carbon Fiber Reinforced Plastic (CFRP) and titanium stacks found in the door surrounds of the aircraft. It was found that a double margin tungsten carbide (WC) cutter with a 1350 point angle and double margin design had superior cost and quality performance as compared to a 1180 point angle polycrystalline diamond (PCD) cutter with a single margin design that was previously used. For this specific application, changing to the proposed WC cutter resulted in savings of approximately 66% per airplane in tool costs alone and a 62% reduction in defects. Second is an investigation into the use of tool kits as a means of providing the manufacturing workforce with commonly needed tools. It was found that kits were not as effective as anticipated in reducing the wasted time from retrieving tools at a central location known as a Tool Crib. To ameliorate this, a series of investigations were conducted, creating analytical tools for identifying shortcomings in the tool kitting distribution system. A team was formed to execute improvements based on the analytical tools developed and achieved a 45% reduction in tools retrieved from outside mechanics' work areas over a 12-week period. / by Jeffrey N. Stein. / S.M. / M.B.A.

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2015. In conjunction with the Leaders for Global Operations Program at MIT. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 51-52). / Aerospace Company X (ACX) is a designer and manufacturer of advanced aerospace systems and its primary customer is the United States Government (USG). In order to reduce cost and minimize risk, both parties have embraced a multi-year contracting model in which productions agreements are signed for up to five-year periods. This allows for significant cost savings over single-year contracts while allowing for predictable production levels for ACX and its suppliers. At the time of this research, the company was soliciting bids from suppliers for the next five-year multi-year contract. Since this is a sole-source situation, ACX must substantiate all costs to justify that the pricing is fair and reasonable. Costs of purchased hardware are substantiated through three primary means: competition, commerciality, and cost-price analysis. Competition is preferred because the pricing can be justified by free-market forces. However, due to intellectual property rights or unique capabilities, suppliers are often contracted as sole-source. The supplier then can claim commerciality (i.e. the part is for sale commercially) or submit for a complete cost review of material, labor, and overhead rates. In some cases the supplier will not release this data to ACX and a government agency performs the review. The success of the cost substantiation phase hinges on getting complete and accurate data from suppliers in a timely manner. This thesis explores the challenges of obtaining cost data from suppliers and proposes recommendations that can be applied to general supplier management situations. First, a metric of proposal adequacy is developed and used to score the adequacy of each received bid. These scores are then analyzed to determine if there is any correlation with the existing enterprise ACX supplier rating system. Finally, recommendations for process improvements are made which focused on communication, IT systems, and standard work. / by David Allen Hahs. / M.B.A. / S.M.